Contact centers frequently employ speech analytics systems to detect the meaning of words spoken during a call by a remote party or an agent of the contact center. Many such systems employ various forms of algorithmic-based processing of digital speech signals to recognize the meaning of words. These speech analytics systems may be referred to as semantic-based speech analytics systems since the speech is analyzed to determine its meaning.
However, research into speech analytics has also suggested that speech can be analyzed to provide non-semantic-based indicators such as, for instance, a speaker's gender, age, personality, emotion, and/or identification. Accordingly, as algorithms that identify such indicators are refined to provide more accurate results, the use of these types of indicators are expected to be more frequently incorporated into contact centers. For instance, customer service applications performed within a contact center may benefit from obtaining non-semantic speech indicators for a call such as knowing the age or gender of a caller. In many instances, a contact center may find it advantageous to deploy a single speech analytics system that is capable of providing both semantic and non-semantic speech indications. Accordingly, it is with respect to these considerations and others that the disclosure herein is presented.